[HTML][HTML] On data processing required to derive mobility patterns from passively-generated mobile phone data

F Wang, C Chen - Transportation Research Part C: Emerging …, 2018 - Elsevier
Passively-generated mobile phone data is emerging as a potential data source for
transportation research and applications. Despite the large amount of studies based on the …

National-Level Multimodal Origin–Destination Estimation Based on Passively Collected Location Data and Machine Learning Methods

Y Pan, A Darzi, M Yang, Q Sun… - Transportation …, 2024 - journals.sagepub.com
Along with the development of information and positioning technologies, there emerges
passively collected location data that contain location observations with time information …

A hybrid of neuro-fuzzy inference system and hidden Markov Model for activity-based mobility modeling of cellphone users

S Rahimipour, M Ghatee, SM Hashemi… - Computer …, 2021 - Elsevier
The aim of this paper is to develop an activity-based travel demand model by receiving
cellular network data. Our contribution is to model the uncertainty of human behaviors and …

Celltrademap: Delineating trade areas for urban commercial districts with cellular networks

Y Zhao, Z Zhou, X Wang, T Liu, Y Liu… - IEEE INFOCOM 2019 …, 2019 - ieeexplore.ieee.org
Understanding customer mobility patterns to commercial districts is crucial for urban
planning, facility management, and business strategies. Trade areas are a widely applied …

Identifying common periodicities in mobile service demands with spectral analysis

C Marquez, M Gramaglia, M Fiore… - 2020 Mediterranean …, 2020 - ieeexplore.ieee.org
In this paper, we investigate the existence and prevalence of comparable dynamics in the
temporal fluctuations for the traffic demands generated by mobile applications. To this end …

CellTrans: Private Car or Public Transportation? Infer Users' Main Transportation Modes at Urban Scale with Cellular Data

Y Zhao, X Wang, J Li, D Zhang, Z Yang - Proceedings of the ACM on …, 2019 - dl.acm.org
Understanding citizens' main transportation modes at urban scale is beneficial to a range of
applications, such as urban planning, user profiling, transportation management, and …

Improved F‐DBSCAN for Trip End Identification Using Mobile Phone Data in Combination with Base Station Density

H Jiang, F Yang, X Zhu, Z Yao… - Journal of Advanced …, 2022 - Wiley Online Library
Trip end identification based on mobile phone data has been widely investigated in recent
years. However, the existing studies generally use fixed clustering radii (CR) in trip end …

An elaborated pattern-based method of identifying data oscillations from mobile device location data

Q Sun, A Darzi, Y Pan - arXiv preprint arXiv:2304.07420, 2023 - arxiv.org
In recent years, passively collected GPS data have been popularly applied in various
transportation studies, such as highway performance monitoring, travel behavior analysis …

[HTML][HTML] Human Mobility Prediction with Calibration for Noisy Trajectories

Q Miao, M Li, W Lin, Z Wang, H Shao, J Xie, N Shu… - Electronics, 2022 - mdpi.com
Human mobility prediction is a key task in smart cities to help improve urban management
effectiveness. However, it remains challenging due to widespread intractable noises in large …

Activity location recognition from mobile phone data using improved HAC and Bi‐LSTM

H Jiang, F Yang, W Su, Z Yao… - IET Intelligent Transport …, 2022 - Wiley Online Library
Existing studies on activity location recognition based on mobile phone data has made great
progresses. However, current studies generally assume constant distance threshold when …